A5046245467- Fault Detection and Control Systems
- Machine Fault Diagnosis Techniques
- Engineering Diagnostics and Reliability
- Impact of AI and Big Data on Business and Society
- Industrial Vision Systems and Defect Detection
- Privacy-Preserving Technologies in Data
Technical University of Denmark
2025
South China University of Technology
2022-2023
Accurate prediction of thermophysical properties is important in chemical engineering, where group-contribution models (GCM) have been used extensively. Traditional GC-based tend to use all available data for parameter estimation, preventing a fair comparison with machine learning (ML) methods that require separate training, validation, and testing data. In this study, we introduce new splitting algorithm which optimally partitions molecular datasets by ensuring comprehensive group...
Deep learning-based methods have been widely used in the field of rotating machinery fault diagnosis. It is practical significance to improve calculation speed model on premise ensuring accuracy, so as realise real-time However, designing an efficient and lightweight diagnosis network requires expert knowledge determine structure adjust hyperparameters network, which time-consuming laborious. In order design networks considering both time accuracy effortlessly, a novel with modified...
The fault diagnosis algorithm can timely detect the faults of devices by monitoring their signals, avoiding greater losses. Deep learning has been widely applied in field diagnosis. However, manually adjusting network structure and hyperparameters requires expert knowledge is laborious time-consuming. In addition, model structures most existing deep methods are complex redundant, which not conducive to operation on hardware with limited computational resources. This paper proposes a...